21 questions
Tooling
2
votes
0
replies
52
views
What are a good books to read in Bayesian Learning
Seems like Bayesian learning is the go to method now for reducing over fitting in ML models, I've read Manning's NLP in action, Deep Learning with python, O'Reilly Deep Learning foundations, Hands on ...
1
vote
0
answers
79
views
model.evaluate() loss metric calculation in Bayesian Neural Net
I am currently trying to set up a Bayesian Neural Net. Hereby, I came across a strange thing.
When compiling my model with the metric keras.metrics.RootMeanSquaredError() and then letting model....
- 21
0
votes
1
answer
204
views
Getting a Bayesian NN to learn the noise within training data and thereby calculating prediction uncertainties
I am trying to train a bayesian NN for noisy time series prediction. I have problems in
getting the model to learn the linear releationship in the data
getting the model to learn the increasing noise
...
- 43
0
votes
0
answers
113
views
Why does my 1D Bayesian CNN, made by replacing the convolution and dense layers with Convolution1DFlipout and DenseFlipout of a working CNN not train?
I have a CNN model that classifies waveforms (of the shape (601,3), where 601 is the number of timesteps while 3 is the number of channels) into noise or signal. It is as follows:
# imports
import ...
0
votes
0
answers
732
views
Pytorch RunTimeError: one of the variables needed for gradient computation has been modified by an inplace operation
I am currently working on a project that involves the implementation of Bayesian GAN. I am following the Pytorch implementation, and this seems to follow the style of the official tutorial of DCGAN. ...
- 2,758
0
votes
1
answer
122
views
I got an error of input type when I use Bayesopt function of Bayesian Optimization Toolbox
I am trying to use Bayesopt for a very simple problem and finding the minimum value of a function
fun = @(x) (x - 3)^2 + 5;
xvar = optimizableVariable('x',[-10,10]);
% Modify the range:
xvar.Range = [...
0
votes
0
answers
92
views
How do I get the probability of a non-categorical variable, given a certain set of parameters?
For example, let's say I have the following conditional probability:
P(competitive=1(yes) | currency=EUR, sellerRating=1000)
If I run the following code, I'll get a probability table:
library(e1071)
...
0
votes
1
answer
149
views
validation loss goes up and down [variational inference]
i was training a mlp through variational inference for a regression task on a small dataset with 1 feature. The nn works and the training loss goes down but the validation loss has random spikes ...
- 197
0
votes
0
answers
485
views
how to make prediction in bayesian convolutional neural network using pyro and pytorch
I'm trying to classify the sign language hand gesture images using Bayesian CNN, I made the following code:
class BCNN(PyroModule):
def __init__(self):
super(BCNN, self).__init__()
...
- 15
0
votes
1
answer
2k
views
Learning multivariate normal covariance matrix using pytorch
I am trying to learn a multivariate normal covariance matrix (Sigma, ∑) using some observations.
The way I went at it is by using pytorch.distributions.MultivariateNormal:
import torch
from torch....
- 166
2
votes
1
answer
591
views
Measuring incertainty in Bayesian Neural Network
Hy everybody,
I'm beginning with tensorflow probability and I have some difficulties to interpret my Bayesian neural network outputs.
I'm working on a regression case, and started with the example ...
- 71
0
votes
1
answer
227
views
Cannot Save Tensorflow_probability model
I'm trying to save the tensorflow model bellow:
Model: "sequential_117"
_________________________________________________________________
Layer (type) Output Shape ...
- 71
0
votes
0
answers
121
views
How to save the predicted data for Bayesian production in r?
I use the below data (not original) & code to do structural bayesian prediction
df1=structure(list(Year = c(1985, 1986, 1987, 1988, 1989, 1990, 1991,
1992, 1993, 1994, 1995, 1996, 1997, 1998, ...
- 77
1
vote
2
answers
5k
views
Do we have an implementation of Bayesian structural time series in Python?
We are looking for a close pythonian implementation of the r library bsts.
To be precise, I'm looking for something that allows me to emulate the functionality of 'add_regressor' from fbprophet.
Have ...
- 21
1
vote
0
answers
237
views
How to get the standard Deviation and mean values after training a BNN model using DenseFlipout Layers in Tensorflow?
After I trained the Bayesian Neural Network model and saved it into a .h5 file, I cannot plot its result because I don't know the standard deviation and predicted mean trained by the model. I'm using ...
- 11